{"id":"W3010608652","doi":"10.1038/s41467-020-15022-4","title":"Prioritizing disease and trait causal variants at the TNFAIP3 locus using functional and genomic features","year":2020,"lang":"en","type":"article","venue":"Nature Communications","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of Allergy and Infectious Diseases; National Human Genome Research Institute; Canadian Institutes of Health Research; Klarman Cell Observatory, Broad Institute; National Institutes of Health; U.S. Department of Health and Human Services; Howard Hughes Medical Institute","keywords":"Linkage disequilibrium; Biology; Genetics; Genome-wide association study; Disease; Allele; Genetic association; Locus (genetics); Single-nucleotide polymorphism; Trait; Computational biology; Haplotype; Genetic architecture; Quantitative trait locus; Gene; Genotype; Medicine; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005745329,0.0004279887,0.0004337776,0.0006874933,0.0003532382,0.0006369457,0.0002625628,0.0003569201,0.0017307],"category_scores_gemma":[0.0006556095,0.0001414135,0.0004923581,0.0005053891,0.0004304042,0.000149107,0.0004455895,0.0005781003,0.000242778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002788058,"about_ca_system_score_gemma":0.0002554595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009037774,"about_ca_topic_score_gemma":0.003227154,"domain_scores_codex":[0.9994835,0.0001090137,0.00005873172,0.0001401642,0.000141039,0.00006750244],"domain_scores_gemma":[0.9993182,0.0003004519,0.0001711468,0.00009145585,0.00004684581,0.00007184855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001508816,0.00003039521,0.00887284,0.00004329348,0.00002892352,0.000101151,0.00002440801,0.0004861071,0.9873461,0.0001132919,0.00002372092,0.002778813],"study_design_scores_gemma":[0.00006267319,0.0006063413,0.1546237,0.00002046595,0.0001778575,0.001908096,0.0001514163,0.01035541,0.8294936,0.0006192557,0.001931939,0.00004923368],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9851623,0.0003099366,0.0124954,0.00005429106,0.000008871533,0.00004553091,0.001002621,0.0001245255,0.000796476],"genre_scores_gemma":[0.9861732,0.0001369215,0.01235529,0.00005410754,0.000003382966,0.00002563783,0.0008914731,0.00002748299,0.0003324088],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0017307,"threshold_uncertainty_score":0.005789816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02745628335687635,"score_gpt":0.2684081191756235,"score_spread":0.2409518358187472,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}